SUMMARY

Animals have to modulate their locomotor behavior according to changes in
external circumstances. The locomotor requirements are expected to be most
extreme for species that move through different physical environments, such as
water versus land.

In this study, we examine the use of the propulsive impulse as a covariate
in the comparison of the kinematics of locomotion of a semi-aquatic frog
Rana esculenta, across land and through water. We focused on the
propulsive phase because it is functionally the most significant phase of the
locomotor cycle in both jumping and swimming, and it is also the most
comparable.

The frog alters the joint angles of its legs in order to adjust its
performance (i.e. impulse) within both locomotor modes. The kinematics and
this modulation of the propulsive phase differ between the two modes; however,
we found that the impulse ranges of swimming and jumping do not fully overlap.
Possible explanations for this include larger lateral forces during swimming,
a reduced force transmission due to a lower external load during swimming and
reduced muscle recruitment due to differences in coordination patterns.

Introduction

Animal locomotion is far from stereotyped. Animals have to modulate their
locomotor behavior according to changes in external circumstances, such as
direction, speed or incline (Biewener and
Corning, 2001; Irschick and
Jayne, 1998). The locomotor requirements are expected to be most
extreme for species that move through different physical environments, such as
water versus land (Biewener and
Gillis, 1999). In spite of the striking differences between
aquatic and terrestrial environments with respect to several physical
properties (Denny, 1993;
Vogel, 1994), many animals use
their limbs to move about successfully both in water and on land. These
semi-aquatic animals occupy a precarious evolutionary position, having to
function in both aquatic and terrestrial environments
(Fish and Baudinette, 1999). If
two tasks require mutually incompatible morphologies of physiologies, it
becomes impossible to simultaneously optimize performance in these two tasks:
natural selection is expected to result in some intermediate phenotype that
provides reasonable performance at both tasks but optimal performance in
neither (Shine et al.,
2003).

Most anurans use their hind limbs to generate propulsive forces during both
jumping and swimming. The same apparatus, the legs, is used to perform the
same task, but in two different media. During both locomotor modes, a forceful
extension of the legs results in an acceleration of the center of mass. Since
this is essentially the same task, the kinematics of the leg segments are
expected to be identical for both locomotor modes. After all, the kinematics
represent the dynamic equilibrium between the internal and external
forces.

Previous studies on anurans (Kamel et
al., 1996; Olson and Marsh,
1998; Gillis and Biewener,
2000) have mainly focused on hind limb muscle function, and have
suggested slightly different functional roles for some muscles, depending upon
the external environment. However, if the goal of the movement is the same for
both locomotor modes (see earlier), but the circumstances are different,
muscle recruitment is bound to be different. This theory seems to be confirmed
by a study on kinematics of swimming and hopping frogs
(Peters et al., 1996), where
no differences were found. However, Peters et al.
(1996) decided to compare the
joint angles at comparable moments in a locomotor cycle, which in turn were
determined by limb configuration (essentially the joint angles as well). By
determining the different phases in this way, however, the data could be
biased. In the present study we have focused on the propulsive phase (the
kick), because it is functionally the most significant phase of the locomotor
cycle in both jumping and swimming
(Nauwelaerts et al., 2001) and
it is the only phase that can be independently determined, i.e. from the
velocity profile of the center of mass.

The major challenge when comparing aquatic and terrestrial locomotion is to
determine which swimming sequence should be compared with which jumping
sequence. This is important because it is known that movement patterns change
within a locomotor mode. Previous studies on kinematics
(Peters et al., 1996) and on
muscle function (Kamel et al.,
1996; Olson and Marsh,
1998; Gillis and Biewener,
2000) compared average sequences, which ignores any
intersequential variation. In many studies on terrestrial locomotion, the
usual covariate used to assess the within-mode variability is locomotor speed.
The drastic difference in the physical properties of the two media, however,
rules out the use of velocity in the comparison of terrestrial and aquatic
locomotion. We therefore propose to add a covariate to the analysis, assuming
that a similar value represents the same `effort' for both locomotor modes. We
suggest that a relevant covariate has to control for (1) differences in the
physical properties of the medium and (2) for differences in the
direction and magnitude of the resultant force of all
external forces (Fig. 1). Both
selection criteria may have significant mechanical consequences on the
locomotor behavior. On land, some of the vertical ground reaction forces
counteract the gravitational forces and result in a vertical acceleration.
These parallel forces dominate and work in the vertical plane, while during
jumping the direction of the movement of the body is at an angle to the
horizontal plane. In contrast, in water, the effective weight of an animal is
reduced by buoyancy, whereas fluid-dynamic forces are drastically increased
(Martinez et al., 1998). Drag
is the resultant force in the orientation of the locomotion, and therefore
works for horizontal swimming in the horizontal plane. During aquatic
locomotion, the resultant external forces are therefore oriented parallel to
the direction of motion.

The theoretical sense and orientation of the external forces for jumping
and swimming frogs, indicated by green arrows. W, weight; GRF, ground reaction
force; L, lift; WRF, water reaction force; D, drag. The red broken line shows
the direction of motion. During jumping, the external forces exerted on the
frog are at an angle to the direction of motion, whereas in swimming, the
external forces are either parallel to or perpendicular to the direction of
motion.

In this study, we evaluate the use of propulsive impulse as a covarying
performance measure that fulfils the two selection criteria above. Impulse is
the change in momentum of a body, and equals the integral of the resultant
force acting on this body over the equivalent time interval:
1
where Fresult is the resultant force, m the mass
and v1 and v2 the instantaneous
velocity at start t1 and end t2,
respectively, of the chosen time interval. This resultant force is the
difference between the propulsive forces Fprop and the
resistive forces, acting against locomotion Fresist,
gravity on land and drag in water. Hence, the propulsive impulse is given by:
2
This equation can be solved based on kinematic data only, and will be used for
both swimming and jumping in order to obtain the propulsive impulses as a
covariate, an independent performance measure.

The purpose of this study is to compare the kinematics of swimming and
jumping in a semi-aquatic frog within the full range of their locomotor
behaviour. Our working hypothesis is that motor control will strive to achieve
similar kinematics for both modes. To make a valid comparison, we will
calculate and evaluate the use of propulsive impulse as a covariate. We expect
the propulsive impulse to be a measure of the `effort' an animal has to
undertake in order to make this movement. Since a full range of impulses was
obtained for both modes, we also expect the ranges of the impulses for both
locomotor modes to overlap.

Materials and methods

Animals

Five frogs Rana esculenta L. (10.8–20.8 g, mean 16.4 g) were
caught in the wild at Groot Schietveld (Brecht, Belgium). The animals were
housed in a glass terrarium and fed a diet of crickets. Temperature within the
holding room was kept at 18°C, and a photoperiod of 12 h:12 h light:dark
was maintained during the holding period. The experimental room was kept at a
temperature of 20–22°C.

Data recording

Jumping

Frogs jumping from an AMTI force plate were simultaneously recorded,
laterally using a high-speed Redlake Motionscope (Redlake MASD, Inc., San
Diego, CA, USA) and dorsally using a NAC-1000 (NAC Image Technology, Inc.,
Tokyo, Japan), both at a frame rate of 500 Hz. The two views were
synchronized. Care was taken to include maximal jumps. For practical reasons,
this set-up did not allow small jumps, so additional (smaller) jumps were
recorded using the Redlake Motionscope system only, with a mirror placed at an
angle of 45° next to the take-off position. The area was lit using a
Tri-lite light (3×650 W; Cool Light Co., Inc., Hollywood, CA, USA). In
both experiments, the surface of the take-off position was covered with fine
sandpaper to prevent the feet slipping.

The following criteria were used to select the sequences. (1) The whole
propulsion phase was visible; (2) both hind limbs extended simultaneously; (3)
in the mirror experiments, jumps were straight and parallel to the mirror. For
each animal, 20 sequences had to pass the selection criteria before concluding
the experiment. These 20 sequences were then screened on their ground reaction
force output, and six sequences for each animal (see
Table 1) were chosen for
further analysis in order to obtain as large a performance range as
possible.

Number of analyzed sequences, range of differences in speed between
start and end of the propulsive phase and mean speed for each
individual

Swimming

Swimming sequences were recorded at 250 Hz using a Redlake Motionscope
system. The frogs were transferred to a swimming tank consisting of two open
tanks (0.5 m × 0.5 m × 0.4 m) connected by a glass tunnel (0.15 m×
0.10 m × 1 m long). The tanks were filled above the level of the
tunnel so that the frogs were compelled to swim completely submerged when
crossing from one tank to the other. A mirror placed beneath the swimming
tunnel allowed both ventral and lateral images to be recorded using a single
camera. The water in the swimming tank was kept at a temperature of 21°C
for the duration of the experiment.

To ensure that the full velocity range was obtained, frogs were stimulated
by touch to swim at maximal speed. The selection of sequences retained for
further analysis was based upon the following three criteria: (1) constant
swimming depth, (2) displacement parallel to, but not touching, the tunnel
walls, and (3) symmetrical hind limb movements.

Again, 20 sequences for each individual were selected. 5–7 sequences
for each animal (see Table 1)
were chosen for further analysis, based upon the velocity range.

Data analysis

Kinematics

For each sequence, the snout tip, cloaca, hip, knee, ankle and midfoot were
digitized, frame by frame, using an APAS (Ariel Performance Analyzing System;
Ariel Dynamics, Inc., Trabuco Canyon, CA, USA). We decided to compare the
kick, which is the only phase of the cycle that is undoubtedly homologous in
the two environments. The kick is defined in this study as the phase in which
the snout tip accelerates. We calculated the three-dimensional (3-D) joint
angles of the hip, knee and ankle for the entire swimming and jumping trials,
but our further analysis was restricted to the data relating to the kick
phase. Time was set to zero when velocity reached its maximum.

To compare the posture of the different segments, the coordinates of the
digitized markers were transformed from a global coordinate system to a new
relative coordinate system that moves (and rotates) with the animal. The
origin of this local coordinate system was situated at the coordinates of the
cloaca, with the X-axis through the trunk of the frog (on the axis
snout–cloaca) and therefore in the direction of the locomotion. The
Y-axis was placed parallel to the perpendicular axis on the
X-axis through the hip. The Z-axis was defined as the cross
product of the X- and Y-axes. The projections of the joint
angles in the XY (the coronal plane), the XZ (the sagittal
plane) and the YZ plane (the transverse plane) were calculated from
these new coordinates (Fig. 2).
In this way, we looked not only at the 3-D joint angles, but also at their
orientation in reference to the trunk. By `immobilizing' the body in a new
coordinate system we were able to compare the leg movements more accurately.
As a result of using this method to calculate the projection angles, however,
it was impossible to determine the hip angle in the YZ plane, as the
hip and trunk segments determine the X- and Y-axis of the
local coordinate system.

3-D joint angles (θHip, θAnkle,θ
Knee) and the local coordinate system in a jumping frog. To
compare the posture of the different segments, the coordinates of the
digitized markers were transformed from a global coordinate system to a new
relative coordinate system that moves (and rotates) with the animal. See text
for a description. The 3-D projection angles in the XY (the coronal
plane), the XZ (the sagittal plane) and the YZ plane (the
transverse plane) were calculated from these new coordinates. The red lines
represent the local coordinate system XYZ, which is also called the
relative coordinate system, while the blue lines indicate the body segments
defined by the digitalization points (the blue circles).

Impulse

The propulsive impulse was calculated as the sum of the mass multiplied by
the velocity change of the snout, and the impulse of the external force acting
against motion.

In terrestrial locomotion, the mass is simply the mass of the frog itself
and gravity is the only external force that has to be taken into account. The
impulse of gravity was calculated as mass × gravitational acceleration
(9.81 m s–2) × duration of the kick δt.
For each sequence of the jumping data, the propulsive impulse was calculated
as the sum of the velocity impulse and the impulse of the gravitational force:
3
where m is mass, g is gravitational acceleration andδ
t is duration of the leg extension. Cos50° was used to
account for the fact that frogs on average jump at an angle of 40° and
thus correction was needed to obtain the external impulse in the direction of
movement. To evaluate the reliability of this kinematically based method, we
compared our calculations with impulse calculations based on the integration
of ground reaction force recordings, calculated by integrating the resultant
force that was filtered using a fourth order Butterworth filter with a cut-off
frequency of 30 Hz.

Calculating the propulsive impulse for the swimming sequences is more
complex. When a body moves through a fluid, it pushes the fluid out of the
way. If the body is accelerated, the surrounding fluid must also be
accelerated. The body behaves as if it were heavier, by an amount called the
hydrodynamic mass (or added mass) of the fluid. Therefore, a correction must
be made for the mass utilising the added mass factor 0.2
(Nauwelaerts et al., 2001),
which is the added mass coefficient (AMC) taken for an ellipsoid body with the
dimensions of a frog's trunk (Daniel,
1984). Drag on the body is the resistive force that must be taken
into account during swimming. The propulsive impulse during swimming was
therefore calculated as:
4
where Cd is drag coefficient (0.14), ρ is density of
the medium (1000 kg m-3), A is area (snout–vent
length)2,
(νmin2+νmax2)/2 is mean
squared velocity, and δt is duration.
Cd=0.14±0.02 (mean ± s.e.m. from
26 sequences) was calculated from the deceleration of the body during the
glide phase. The Cd can be calculated in this manner
because drag is the only external force during the glide phase, and the
velocity of the center of mass is known
(Bilo and Nachtigall, 1980;
Stelle et al., 2000).

Statistical analysis

To evaluate the method of calculating the impulse from the digitization
data, impulse values were compared in pairs with those obtained by integrating
the ground reaction force. The two methods were compared and then
statistically substantiated using a Method Validation Tool Kit
(http://www.westgard.com/mvtools.html),
using a paired data calculator. The resulting value for the observed bias was
tested for significance using a Student t-test
(Westgard, 1995).

The 3-D and projection angle profiles (angles against time) were tested for
differences between the two locomotor modes, examining not only average
differences in profiles sensus strictus, but also differences in angle
profiles with respect to changes in impulse, using a linear mixed model
(ANCOVA) in SAS version 10.0 for Microsoft Windows. This model compared the
profiles after adjustments (1) for individual differences, and (2) for
correlations of the angles within a sequence (a first order autoregressive
covariance-structure). A general Sattherthwaite method was used for correcting
the degrees of freedom.

Significant interactions (1) between mode, time and impulse were
interpreted as differences in the linear changes in impulse modulation, and
(2) between mode, time2 and impulse as differences in how the shape
of the profiles were affected by impulse. A second analysis, within one
locomotor mode, was performed using the same linear model to enable us to
describe the profiles (angle vs time and angle vs
time2) and changes in these profiles that lead to a different
impulse for each mode.

Results

Method validation

There was no significant difference between the two methods of calculating
the propulsive impulse for jumping. The calculated bias of the test method
(impulses from digitization data), the value of systematic error, was–
0.0014, but did not differ significantly from zero
(t=–1.2389, P=0.23). Random error
(s.d.differ) between the methods, due to imprecisions of
both methods and matrix effects, was 0.0053.

Impulses

Although a large range of impulses was obtained for both locomotor modes,
the impulses of the propulsion force were greater in jumping (between 0.018
and 0.053 kg m s–1) than in swimming (between 0.005 and 0.026
kg m s–1). Despite a large overlap in duration, there is
little overlap in the impulse–duration graph for the two modes (impulse
overlap range = 0.018–0.026 kg m s–1)
(Fig. 3).

Differences in impulse between swimming and jumping. There is no
relationship between the impulse of the propulsion force and the duration of
the propulsive phase within a locomotor mode. The range of the duration of the
propulsive phase is greater in swimming, but there is a considerable overlap
in the duration of both modes. The impulse gained during jumping is greater,
and there is a small overlap area with swimming impulse.

Kinematics

Mean joint angles within modes

All 3-D joint angles have a significant, linear change with time (see
columns T, Table 2), even after
Bonferroni correction in both locomotor modes. The angle patterns are shown in
Fig. 4, where 3-D angle is
plotted against time (time set to zero at maximal velocity). The effect of
impulse is shown along the Y-axis.

Surface plots of 3-D hip (A,B), knee (C,D), ankle (E,F) joint angle
profiles against impulse during the propulsive phase in both jumping (A,C,E)
and swimming (B,D,F). The angle axis is scaled between zero (fully flexed) and
180° (fully extended). Time is set to zero at the end of the propulsive
phase, when maximal velocity is reached. An interactive effect with impulse
becomes visible when the colour scheme does not follow the axes of the plot.
The key indicates the colour codes for the angles (in degrees) on the
Z-axis.

The projection angles show that most movement occurs in the XY
plane (the coronal plane) and the YZ plane (transverse plane).

Mean joint angles between modes

The traditional method for comparing kinematic profiles is to compare the
average profile from different situations. Here, the mean slopes of the hip
and knee 3-D angle–time profiles differ significantly (see column
T×Mode of Table
2A) between the two modes, which indicates a difference in angle
velocity or a difference in timing of the extension during the propulsive
phase. These dissimilarities are for the knee and ankle due to differences in
the slope of the angle–time curves in the XY plane, i.e. the
coronal plane through the trunk. However, these significant differences
disappear after Bonferroni correction.

The shape of the angle–time curve (column
T2×Mode) only differs for the hip XY angle:
during swimming this angle changes linearly over time, while during jumping a
significant curvature is found.

This means that the conventional method of comparing the kinematics, that
is without taking into account the variation within a locomotor mode, does not
yield any differences between the kinematics of jumping and swimming in R.
esculenta.

Influence of impulse on the kinematic profiles

The intersequential variation is considerable (see
Fig. 5). When impulse is added
to the analysis, most of the intersequential variation can be explained. The
3-D knee and 3-D ankle angle profiles change significantly with impulse, and
this change differs between swimming and jumping. For the knee joint, during
jumping, the kinematic profiles change with impulse in the XY and
YZ plane, whereas during swimming the change with impulse also occurs
in the XY and XZ plane. For the ankle, a trend with impulse
is obtained in the XY and XZ plane in both modes, but this
modulation differs in the XY plane. In the hip joint, modulation of
the 3-D angle differs due to a linear and parabolic change during swimming,
and a slight parabolic change during jumping. The difference mainly occurs in
the XY plane.

Mean kinematic profiles of hip (black), knee (red) and ankle (blue) joints
during jumping and swimming. The thick lines represent the mean profile, the
thin lines indicate ± s.d. The total time of each propulsive
phase is set at 100%.

Joint angle profiles between modes with respect to impulse

Most angles change with impulse (see columns T×L of
Table 2), which means that to
look solely at the average profiles is to overlook a significant source of
variation within a locomotor mode. Therefore, for the remaining angles,
profiles of different modes should be compared with respect to the impulse.
The unexpected finding that the impulse ranges only display a partial overlap
means that the overlapping range is based on a limited data set. For the hip,
this comparison results in a larger angle (15°) of the hip at the
beginning of the propulsion phase of jumping. This means the hip is more
flexed at the start position, probably due to the weight of the trunk on the
legs, because this difference in angle is the greatest in the XY
plane. Although the knee is extended more and flexed less in the XY
plane during swimming, this effect is compensated for by the fact that the
knee does not move in the YZ plane during swimming, whereas during
jumping, the knee displays considerable movement (60°). This results in a
slightly more flexed knee during swimming, but a less extended knee at the end
of the propulsive phase, producing the same range of movement for both
locomotor modes in 3-D. The ankle flexes more during swimming (15°),
because the ankle XY projection angle is smaller at the start and
extends more slowly during swimming and because the ankle extends more during
jumping in the YZ plane.

Discussion

Similar to previous studies of the kinematics of swimming and jumping in
frogs (Peters et al., 1996),
our mean profiles do not differ. A major issue in such a comparison of means,
however, is that factors other than the difference in medium can induce
considerable variation, as illustrated in
Fig. 5 (s.d. is
large). As shown, significant differences between locomotor modes can be
overlooked if this variation is ignored.

In locomotion, it is known that the performance level, for example
locomotor speed or jumping distance, is an important source of variation.
Kinematic characteristics change with speed and a convenient solution is to
add speed as a covariate in the kinematic analyses (e.g.
Hoyt et al., 2000;
Vanhooydonck et al., 2002).
Swimming at a certain speed is not similar to performing at the same speed on
land, however, because (1) the two media, i.e. water and air, differ
drastically in their physical properties, and (2) the musculoskeletal system
has to act against different substrates, namely viscous water versus
solid ground.

Jumping distance and swimming speed can be considered the overall
collective result of a more basic performance measure, namely the forces
transmitted by the feet to the substrate. These forces are necessary in order
to accelerate the body, and in case of swimming, to accelerate the added mass.
These forces are also required to overcome resistive forces (gravity and drag)
during the propulsive kick in both locomotor modes. Therefore, the use of the
propulsive impulse as a covarying performance measure potentially permits a
sound comparison of swimming and jumping. This converts the kinematic analysis
into the comparison of two 3-D surface plots per joint, one for each medium
(see Fig. 4).

For the sequences that result in a similar propulsive impulse, the
kinematics of swimming and jumping differ significantly. As for the 3-D
angles, these differences remain small, but the configuration with respect to
the animal's body differs. It seems that moving from land to water coincides
with a rotation in the hip joint, turning the knee more outwards and resulting
in different foot positions. However, this comparison was only based on a
limited data set. The initial expectations were that the performance ranges
for swimming and jumping would largely overlap, because an effort was made to
obtain the full range of performances for both locomotor modes (see Materials
and methods). However, the performance overlap is surprisingly small (see
Fig. 3) and the impulses for
jumping are considerably higher than for swimming.

One possible explanation for this difference in impulse is that our
kinematically based estimations of the propulsive impulse are unreliable for
either or both locomotor modes. For jumping, however, the kinematic method
yielded similar results to those obtained via integration of the
ground reaction forces (i.e. the more conventional method). This gave support
to the kinematic method and the obligatory method of analyzing the swimming
bouts. There are two potential sources of error in this model: the drag
coefficient and the added mass coefficient (see equation 4). The drag
coefficient was obtained from the deceleration of the body during the glide
phase. It is possible this causes an underestimation of the
Cd because during the propulsive phase, the body is not in
such a streamlined posture. However, in order to obtain swimming impulses
within the range of the impulses of the jumping trials, a 14-fold increase of
the Cd is required, which would correspond to the drag
coefficient of a square cylinder normal to the flow. Such a large drag
coefficient is impossible for a frog's body. The second potential source of
error is the added mass coefficient, which might also be underestimated.
Again, to make the impulses overlap would require a unrealistically high value
and greatly exceed the values previously used
(Daniel, 1984;
Gal and Blake, 1988;
Nauwelaerts et al., 2001).
Moreover, the chosen drag coefficient and added mass coefficient have already
been succesfully used to mimic the displacement profiles of swimming frogs
(Nauwelaerts et al., 2001).
Therefore, we can assume that the difference in propulsive impulse is real and
not caused by an unrealistic model for the swimming bouts.

Thus, the calculated impulse ranges differ. This leaves us with
three possible explanations. First, the present kinematically based impulse
calculations are equivalent to the time integral of the force components in
the direction of the observed displacement only. Force components
perpendicular to the direction of motion, but cancelling each other, might be
transmitted to the substrate. These forces do originate from muscular action
but do not result in a change in momentum, nor are they used to overcome
resistive forces. They therefore do not show up in the impulse estimations. In
symmetrical jumping, for instance, lateral forces exerted by left and right
foot (if present) cancel each other. From this point of view, maximal swimming
and maximal jumping might yield comparable efforts at the muscular level, but
these efforts might be translated into largely differing propulsive
impulses because of larger non-propulsive force components being transmitted
to water during swimming. If true, this reduced transmission efficiency can
presumably be linked to the fact that frogs are secondary swimmers, primarily
adapted to a terrestrial, saltatory motion
(Wake, 1997). It is remarkable
that fully aquatic frogs like Xenopus have entirely different leg
configurations, presumably to circumvent this problem, but inhibiting their
jumping ability (Trueb, 1996).
The kinematic shift observed in Rana esculenta brings the legs into a
more Xenopus-like configuration, but this might not be sufficient to
equalize the impulse ranges for this semi-aquatic frog.

Alternatively, it should be considered that comparable efforts at the
muscular level result in an overall decreased force transmission to the
substrate during swimming, which logically ends in lower impulses. Such
conditions can occur when muscles have to act against lower external loads:
contraction will proceed more rapidly but, as a consequence of the
force–velocity relationship, less forcefully. The external load acting
on the muscle system of the legs derives from two sources: the inertial load
(due to the change in momentum) and the load resulting from the resistive
forces. If, for the sake of argument, we assume that for the fastest swimming
kick and the longest jump both the muscular effort and activation are
maximized, we can compare the external loads for a frog of about 0.02 kg by
making use of the formulae presented in Equations 3 and 4. It appears that
both the average inertial load and the average resistive load are about twice
as high for jumping (inertial: 0.42 N versus 0.21 N; resistive: 0.12
Nversus 0.07 N), which gives support to this alternative explanation
based on the force–velocity relationship of muscular contraction.
However, if this holds true, contraction velocities or joint extension
velocities should be higher for the swimming sequences. This is not confirmed
by Gillis and Biewener (2000),
who found no strain rate differences between swimming and jumping for the
muscles examined, nor by the data in the present study. When we compare the
velocity patterns of the maximal jumping and the maximal swimming trial for
each frog, joint velocities were found to be significantly higher for the
jumping sequences (paired t-test; P<0.05).

Finally, we consider the possibility that estimates of the propulsive
impulses are a good measure of the effort made by the frog's leg muscles, but
that some of the muscles become less activated, even when performance is
maximized. This would be analogous to a terrestrial animal attempting to move
on a slippery surface, such as ice. To optimize movement, recruitment is
reduced so as not to exceed static friction. This is possible when maximized
contraction, optimal for jumping, would cause less coordinated, ineffective
movement patterns during swimming, resulting in an even more feeble
performance than with reduced recruitment. This seems plausible given the
difference in external load and taking into account that frogs are primarily
adapted to terrestrial locomotion (Wake,
1997).

When we look at Fig. 6,
coordination does differ between the locomotor modes. During swimming, all
joints are active at the same moment, at approximately 70% of the total
propulsive phase, whereas during jumping the hip extends first (halfway the
propulsive phase), followed by a synchronous action of knee and hip. To
prolong the acceleration phase during jumping, a proximo–distal
succession of the joint actions is favourable, causing the maximal velocity to
be reached as late as possible during push-off
(van Ingen Schenau, 1989).
However, a synchronous extension of all joints, as during swimming, enables a
higher maximal velocity to be reached
(Alexander, 1989). It is
plausible that for swimming, attaining a higher velocity is more important
than the timing of this velocity peak. Interestingly, the coordination pattern
found for R. esculenta differs from the one described by Gillis and
Blob (2001) for Bufo
marinus, a more terrestrial species. In these toads, limb extension
begins at the knee during swimming. In contrast, during jumping the hip
precedes extension at more distal joints, which is similar to R.
esculenta's coordination. When the coordination of the two locomotor
modes is different, muscle activation patterns are also expected to differ.
Gillis and Biewener (2000)
found lower EMG intensities for the m. plantaris (primarily an ankle
extensor), and a shorter EMG burst duration for the m. cruralis (primarily a
knee extensor) during swimming in Bufo marinus. From our data, it
appears that the knee and ankle are fairly conservative joints. Despite
differences in starting angle, they have a similar movement range in both
locomotor modes. If we assume that EMG patterns are similar in Rana
esculenta, this finding may point at an active modulation. Yet, it must
be taken into account that the EMG data of Gillis and Biewener
(2000) refer to averages over a
performance range, and it is not specified whether maximal performance is
included. Assuming, however, that the reported lower and shorter
EMG-activations also occur at maximal performance, a smaller plantaris and
cruralis muscle might suffice for swimming. Again, a comparison with a fully
aquatic frog like Xenopus might be very helpful.

The first derivatives of the kinematic profiles show that the coordination
between the two locomotor modes differs slightly. The colour codes are the
same as for Fig. 5. The hip
action is earlier in the movement during jumping. Although a
proximo–distal succession of the joints is optimal during jumping, the
timing of the knee and ankle action is similar. During swimming, all joints
are synchronously active.

In conclusion, the kinematically based impulse calculations are a promising
tool in the comparison of drastically different locomotor modes, but do not
tell the full story. The unexpected finding of the largely non-overlapping
impulse ranges in swimming and jumping raises new questions. The formulated
hypotheses are not mutually exclusive and the discussed phenomena might act
together. Although we agree that the kinematically based method is a
simplification of reality, we argue that this alone could not explain the
observed discrepancy. Without disregard for other explanations, we believe
that the concept of non-propulsive impulses being much larger in swimming than
in jumping is the most plausible. One step towards the solution would be to
map all the external forces involved in both locomotor modes. In a terrestrial
environment, the external forces consist of the gravitational forces and the
ground reaction forces, which should be measured for both feet separately.
Determining the external forces in an aquatic system is far more complex and
requires a special setup, i.e. studying the flow induced by the frog's
movements. It would also be interesting to investigate whether the same EMG
patterns and strain rate profiles as described for B. marinus
(Gillis and Biewener, 2000)
occur in a semi-aquatic frog such as R. esculenta. Since the
coordination patterns are different, the possibility exists that we cannot
simply use Gillis and Biewener's results to interprete our data. There remain
a few problems with the use of the propulsive impulse as a covariate in the
comparison between aquatic and terrestrial sequences. It is not easy to
determine a comparable level of effort when examining two locomotor modes in
such different physical environments. A measure for power input, the active
metabolic rate (Fish and Baudinette,
1999), or the metabolic cost of transport, could be better
estimates for the `effort' exerted during the propulsive phase. However,
measuring instantaneous oxygen consumption in frogs is not straightforward.
These are all challenges for future research.

ACKNOWLEDGEMENTS

We would like to thank Jan Scholliers for his help during the experiments
and for taking care of the animals. Ann Hallemans contributed to this paper by
writing a Matlab program to calculate the projection angles in a body bound
coordinate system. Willem Talloen wrote the SAS program to perform the
statistical analyses, while Kristiaan D'Août helped with some of the
figures. We are also grateful to Joe Carragher for his comments on earlier
versions of the manuscript. We wish to express our gratitude to the three
anonymous referees for their valuable comments. This work was supported by
grants of GOA-BOF to P.A. and IWT to S.N.

Fish, F. E. and Baudinette, R. V. (1999).
Energetics of locomotion by the Australian water rat (Hydromys
chrysogaster): a comparison of swimming and running in a semi-aquatic
mammal. J. Exp. Biol.202,353
-363.

Similar articles

Other journals from The Company of Biologists

Many organizations that use sonar for underwater exploration gradually increase the volume of the noise to avoid startling whales and dolphins, but a new Research Article from Paul Wensveen and colleagues reveals that some humpback whales do not take advantage of the gradual warning to steer clear.

Many animals stabilize their vision by swivelling their eyes to prevent the image from smearing as they move. A new Research Article on tadpoles from Céline Gravot and colleagues shows that contrast between objects in their view affects the strength of this visual reflex, suggesting that the eye may be processing the image at a basic level to produce the reflex.

When starting her own lab at James Cook University, Australia, Jodie Rummer applied for a Travelling Fellowship from JEB to gather data on oxygen consumption rates of coral reef fishes at the Northern Great Barrier Reef. A few years later, Björn Illing, from the Institute for Hydrobiology and Fisheries Science, Germany, followed in Jodie’s footsteps and used a JEB Travelling Fellowship to visit Jodie’s lab. There, he studied the effects of temperature on the survival of larval cinnamon clownfish. Jodie and Björn’s collaboration was so successful that they have written a collaborative paper, and Björn has now returned to continue his research as a post-doc in Jodie’s Lab. Read their story here.

Where could your research take you? The deadline to apply for the current round of Travelling Fellowships is 30 Nov 2017. Apply now!